Principled Optimization Of Dynamic Neural Networks

This dissertation generalizes the specialized compilation techniques applied to static dataflow graphs, the predominant programming model of deep learning, to fully dynamic neural networks. Contributions include an intermediate representation for dynamic neural networks, a set of general optimizations as well as specialized dynamic optimizations, and an efficient runtime for dynamic neural networks.